4.6 Article

Identification of a Six-Immune-Related Long Non-coding RNA Signature for Predicting Survival and Immune Infiltrating Status in Breast Cancer

Journal

FRONTIERS IN GENETICS
Volume 11, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fgene.2020.00680

Keywords

breast cancer; immune infiltration; long non-coding RNA; gene expression omnibus; the cancer genome atlas; prognostic signature

Funding

  1. National Natural Science Foundation of China [81672613, 81874119]
  2. Special Foundation for Taishan Scholars [ts20190971]
  3. Special Support Plan for National High Level Talents (Ten Thousand Talents Program) [W01020103]
  4. National Key Research and Development Program [2018YFC0114705]
  5. Qilu Hospital Clinical New Technology Developing Foundation [2018-7, 2019-3]

Ask authors/readers for more resources

Long non-coding RNAs (lncRNAs) play critical roles in tumor immunity; however, the functional roles of immune-related lncRNAs in breast cancer (BC) remain elusive. To further explore the immune-related lncRNAs in BC, whole genomic expression data and corresponding clinical information were obtained from multiple BC datasets. Based on correlation with the immune-related genes within the training set, we screened out the most promising immune-related lncRNAs. Subsequently, Lasso penalized Cox regression analysis followed by stepwise multivariate Cox regression analysis identified six survival-related lncRNAs (AC116366.1, AC244502.1, AC100810.1, MIAT, AC093297.2, and AL356417.2) and constructed a prognostic signature. The cohorts in the high-risk group had significantly poor survival time compared to those in the low-risk group. In addition, a nomogram integrated with clinical features and the prognostic signature was developed on the basis of the training set. Importantly, all the findings had a similar performance in three validated datasets. In the following studies, our integrative analyses indicated that the infiltration of CD8-positive (CD8) T cells associated with a good prognosis was strikingly activated in the low-risk group. To further provide an interpretation of biological mechanisms for the prognostic signature, we performed weighted gene co-expression network analysis (WGCNA) followed by KEGG pathway-enrichment analysis. Our results showed that the antigen presentation pathway involved in protein processing in endoplasmic reticulum and antigen processing and presentation was markedly altered in the high-risk group, which might promote tumor immune evasion and associate with poor clinical outcomes in BC patients with high risk scores. In conclusion, we aimed to take advantage of bioinformatics analyses to explore immune-related lncRNAs, which could function as prognostic indicators and promising therapeutic targets for BC patients.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.6
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available